事件驱动的带执行器无线传感器网络分簇算法研究

带有执行器的无线传感器网络是指在传统无线传感器网络中加入执行节点,形成传感器节点、执行节点和基站共同构成的三层监控网络。根据执行器在能量、计算能力和感知能力方面的优势,提出建立应用于事件调度的双环分簇算法。算法将执行器连接成双环结构,提升网络在线扩展能力的同时,也为无线传感器网络满足事件驱动构建基础。仿真实验证明,此算法能够有效降低网络能耗,随着节点数目的增加和监控领域的扩大,表现更加凸出。     

基于空间相关性的事件驱动无线传感器网络分簇算法

分簇算法是传感器网络中减少能量消耗的一种关键技术,它能够增强网络的扩展性和延长网络的生存时间。针对传感器节点数据的空间相关性,该文提出了一种新的基于空间相关性的事件驱动传感器网络分簇算法。算法根据用户要求的误差门限及结合节点数据的空间相关性马尔可夫模型,将事件感知区域划分成虚拟极坐标等价层。每个等价层选取层内当前剩余能量最大的节点作为簇头,网络通过移动代理收集簇头感知信息,该方法减少了传输数据量,有效节省了网络能量。     

基于空间相关性的事件驱动无线传感器网络分簇算法

分簇算法是传感器网络中减少能量消耗的一种关键技术,它能够增强网络的扩展性和延长网络的生存时间。针对传感器节点数据的空间相关性,该文提出了一种新的基于空间相关性的事件驱动传感器网络分簇算法。算法根据用户要求的误差门限及结合节点数据的空间相关性马尔可夫模型,将事件感知区域划分成虚拟极坐标等价层。每个等价层选取层内当前剩余能量最大的节点作为簇头,网络通过移动代理收集簇头感知信息,该方法减少了传输数据量,有效节省了网络能量。     

基于动态簇半径的非均匀分簇算法

在无线传感器网络分簇路由算法中,针对节点能耗不均衡所引发的"热区"问题,提出了基于动态簇半径的非均匀分簇算法(UCDCR)。该算法在簇组建阶段,对网络进行区域划分,不同区域的候选簇首通过簇竞争半径来构建大小不同的簇,使簇首随网络的运行动态的改变簇竞争半径,为数据转发预留更多能量。仿真结果表明:与EEUC算法和CUCRA算法相比,UCDCR算法更加有效地均衡了节点能耗,延长了网络生命的周期。     

新的无线传感器网络分簇算法

针对无线传感器网络节点能量受限的特点,提出了一种响应式分布分簇算法(RDCA,responsive distributedclustering algorithm).该算法不需预先得知节点自身及其他节点的位置信息,而仅根据局部拓扑信息快速进行分布式的簇头选举,并根据代价函数进行簇的划分,适用于周期性获取信息的无线传感器网络.分析与仿真表明,该算法具有良好的负载平衡性能和较小的协议开销,与LEACH协议相比,能够减少能量消耗,网络生存期大约延长了40%.     

基于权值的无线传感器网络分簇算法

综述了无线传感器网络路由算法的主要成果,但重点分析更具有能量有效性的分簇路由算法,对各种算法的主要思想进行了性能评价,提出了一种新的算法.     

无线传感器网络中基于自适应定时器策略的分簇算法

提出了一种适用于无线传感器网络的基于自适应定时器策略的分簇算法,该算法通过自适应调整节点的等待时间来保证较多电池能量的节点有更大的机会成为簇首.理论分析表明该算法不仅实现了系统的动态负载均衡,并且能够通过参数的设置确保簇首的均匀分布.仿真结果显示该算法有效地延长了系统生命,提高了网络的能耗效率.     

面向目标跟踪的无线传感器网络动态分簇

在考虑节点剩余能量和节点探测信号强度的基础上,提出了一种面向目标跟踪的无线传感器网络动态分簇方法。由于在簇首选择时考虑了节点的剩余能量,因此可以有效地避免簇首节点能量不足导致的跟踪失败。方法既能保证各个节点均衡地担任簇首节点,又能避免簇首切换过于频繁,因此可以延长网络的使用寿命。计算机仿真结果表明,在满足簇首节点能量需求和簇内节点大部分能观测到目标的情况下,应该取尽量小的能量阈值和尽量大的距离阈值。     

无线传感器网络分簇算法分析与性能比较

文中在介绍无线传感器网络路由协议的基础上,重点分析了几种有代表性的分簇路由协议算法。然后对各种分簇算法从10个评价参数上进行了一个综合对比,总结了无线传感器网络现有分簇路由协议的优点和存在的问题。最后从网络安全性和协议的实用性等方面,并对无线传感器网络分簇路由协议算法进行了展望。     

基于感应数据值的无线传感器网络分簇算法

提出了一种无线传感器网络的分簇算法,用于协助基于簇的入侵检测方案检测网络中的各种恶意攻击行为.它将整个网络划分成若干个簇,使得簇内各传感器节点物理位置临近,并且采集的数据值接近.这一特性使得识别异常节点非常容易,并且保证入侵检测方案具有较高的检测精度和较低的误报率.该算法也使得网内数据处理变得异常简单,从而能够有效节省传感器节点的能量,延长网络的寿命.     

An energy efficient clustering routing algorithm for wireless sensor networks

~~An energy efficient clustering routing algorithm for wireless sensor networks1. Mainwaring A, Polastre J, Szewczyk R, et al. Wireless sensor networks for habitat monitoring. Proceedings of the ACM International Workshop on Wireless Sensor Networks and A…     

WSN中能量有效分簇多跳路由算法

针对现有无线传感器网络(WSN)分簇路由算法存在的能耗不均衡问题,提出一种能量有效分簇多跳路由算法,该算法包括两个方面:一是选举簇首时引入簇内平均剩余能量因子,根据上一轮结束后簇内各节点剩余能量和簇内节点的平均剩余能量的比值更新簇首在所有节点中所占的百分比;二是要求簇首根据MTE多跳路由协议与基站通信,从而均衡WSN整...     

Energy-efficiency clustering protocol in wireless sensor networks

The conventional clustering method has the unique potential to be the framework for power-conserving ad hoc networks. In this environment, studies on energy-efficient strategies such as sleeping mode and redirection have been reported, and recently some have even been adopted by some standards like Bluetooth and IEEE 802.11. However, consider wireless sensor networks. The devices employed are power-limited in nature, introducing the conventional clustering approach to the sensor networks provides a unique challenge due to the fact that cluster-heads, which are communication centers by default, tend to be heavily utilized and thus drained of their battery power rapidly. In this paper, we introduce a re-clustering strategy and a redirection scheme for cluster-based wireless sensor networks in order to address the power-conserving issues in such networks, while maintaining the merits of a clustering approach. Based on a practical energy model, simulation results show that the improved clustering method can obtain a longer lifetime when compared with the conventional clustering method.     

Node correlation clustering algorithm for wireless multimedia sensor networks based on overlapped FoVs

In this paper, a clustering algorithm is proposed based on the high correlation among the overlapped field of views for the wireless multimedia sensor networks. Firstly, by calculating the area of the overlapped field of views （FoVs） based on the gird method, node correlations have been obtained. Then, the algorithm utilizes the node correlations to partition the network region in which there are high correlation multimedia sensor nodes. Meanwhile, in order to minimize the energy consumption for transmitting images, the strategy of the cluster heads election is proposed based on the cost estimation, which consists of signal strength and residual energy as well as the node correlation. Simulation results show that the proposed algorithm can balance the energy consumption and extend the network lifetime effectively.     

采用自适应退避机制的无线传感网分簇算法

传统的LEACH算法因为簇首选举的随机性而导致节点能量分布不均,从而影响网络寿命和系统吞吐量,在此基础之上提出了一种基于自适应退避机制的分簇算法,通过设定一个能量门限来衡量簇首的健康度,并采用退避机制来使那些趋于衰亡的簇首能找到合适的继任者来担当簇首,保证数据传输的可靠性.仿真实验显示,该算法能够较LEACH获得更长的网络寿命,并提高了网络的吞吐量.     

基于遗传聚类的无线传感器负载均衡路由算法

通常的无线传感器分簇网络存在节点负载不均衡的问题。为均衡各节点能量消耗,延长网络生存周期,将K均值算法与遗传算法相结合,提出一种负载均衡的无线传感器网络路由算法,算法利用遗传算法的全局寻优能力以克服传统K均值算法的局部性和对初始中心的敏感性,实现了传感器网络节点自适应成簇与各节点负载均衡。仿真实验表明,该算法显著延长了网络寿命,相对于其他分簇路由算法,其网络生存时间延长了约43%。     

An optimised fuzzy clustering for wireless sensor networks

Minimising energy consumption has always been an issue of crucial importance in sensor networks. Most of the energy is consumed in data transmission from sensor nodes to the base station due to the long distance of nodes from the base station. In the recent past, a number of researchers have proposed that clustering is an efficient way of reducing the energy consumption during data transmission and enhancing the lifetime of wireless sensor networks. Many algorithms have been already proposed for cluster head selection. In this work, we analyse and compare the lifetime of the network with three different fuzzy-based approaches of cluster head selection. The three strong parameters which play an important role in lifetime enhancement – energy, centrality and node density – are considered for cluster head selection in our proposed fuzzy approaches. In the first approach, energy and centrality are considered simultaneously in a fuzzy system to select the cluster heads. In the second approach, energy and node density have been taken in a fuzzy system to select the cluster heads. In the third approach, node density and centrality are considered simultaneously by a fuzzy system to select the cluster heads. Simulation results of these fuzzy logic-based approaches show that all the three approaches are superior to the Low-Energy Adaptive Clustering Hierarchy (LEACH). Simulation results also show that the energy-centrality-based fuzzy clustering scheme gives best performance among all the three fuzzy-based algorithms and it enhances the lifetime of wireless sensor networks by a significant amount.     

基于遗传聚类的无线传感器负载均衡路由算法

通常的无线传感器分簇网络存在节点负载不均衡的问题。为均衡各节点能量消耗,延长网络生存周期,将K均值算法与遗传算法相结合,提出一种负载均衡的无线传感器网络路由算法,算法利用遗传算法的全局寻优能力以克服传统K均值算法的局部性和对初始中心的敏感性,实现了传感器网络节点自适应成簇与各节点负载均衡。仿真实验表明,该算法显著延长了网络寿命,相对于其他分簇路由算法,其网络生存时间延长了约43%。     

Design guidelines for wireless sensor networks: communication, clustering and aggregation

When sensor nodes are organized in clusters, they could use either single hop or multi-hop mode of communication to send their data to their respective cluster heads. We present a systematic cost-based analysis of both the modes, and provide results that could serve as guidelines to decide which mode should be used for given settings. We determine closed form expressions for the required number of cluster heads and the required battery energy of nodes for both the modes. We also propose a hybrid communication mode which is a combination of single hop and multi-hop modes, and which is more cost-effective than either of the two modes. Our problem formulation also allows for the application to be taken into account in the overall design problem through a data aggregation model.     

无线传感器网络分簇路由协议研究

在无线传感器网络中,分簇型路由在路由协议中占据重要的地位,该协议方便拓扑结构管理,能源利用率高,数据融合简单。文章从簇头生成、簇形成和簇路由3个角度对典型的分簇路由算法LEACH,HEED,EEUC,PEGASIS进行了系统描述,从网络生命周期和节点存活数量等方面,对比了其优缺点,结合该领域的研究现状,指出了未来研究的方向。